Eaton announced, on January 26, 2026, the intent to separate its Mobility Group (including both the Vehicle and eMobility segments) into an independent, publicly traded company. We expect to complete the separation by the end of the first quarter of 2027. As a standalone company, the Mobility business will be more focused and agile, creating exciting opportunities for employees to grow, innovate, and help shape the future of mobility. The separation reflects strong confidence in the Mobility team and positions the new company as an employer of choice in the automotive and commercial vehicle industry.
The compensation and benefits that will initially be offered for this position are based on Eaton's plans, programs and practices. If you are offered and accept this position and are actively employed by the Mobility Group when the spinoff closes, the new company will provide further details to employees concerning compensation and benefits at that time.
Eaton Corporation’s Center for Intelligent Power has an opening for a Senior Engineer- Machine Learning Engineering. The ideal candidate will be responsible for end to end engineering, deployment, monitoring and maintaining the machine learning model at scale. This position requires understanding in machine learning and software engineering. The candidate will work closely with other teams to make sure the requested features by the businesses are delivered.
About Eaton:
Eaton is power management company with 2018 sales of $21.6 billion. We make what matters work. Everywhere you look—from the technology and machinery that surrounds us, to the critical services and infrastructure that we depend on every day—you’ll find one thing in common. It all relies on power. That’s why Eaton is dedicated to improving people’s lives and the environment with power management technologies that are more reliable, efficient, safe and sustainable. Because this is what matters. We are confident we can deliver on this promise because of the attributes that our employees embody. We’re ethical, passionate, accountable, efficient, transparent, and we’re committed to learning. These values enable us to tackle some of the toughest challenges on the planet, never losing sight of what matters.
- Develop and maintain Data Engineering pipelines, continuous integration, and deployment (CI/CD) pipelines for machine learning models.
- Understanding the challenges in productionizing machine learning software and collaborating with data scientists to ensure that the software best practices, templates and other ML principles are integrated to reduce cycle time.
- Develop and maintain documentation and training materials for machine learning solutions.
- Keep up to date with emerging technologies and trends in data engineering and cloud infrastructure.
